• Pratik Ghatte
• Tushar Madane
• Vedant Phadtare
• Chetan Kholgade
• Shrikant Shinde

Plant Health monitoring and disease detection is essential for sustainable agriculture. Effective plant disease detection can greatly reduce the use of toxic chemicals, pathogens by identifying the diseases associated with infected plants and thereby increasing agriculture farming and leading to a better environment. Pathogens causing plant diseases include viruses, fungi, bacteria which are the main sources of causing diseases in plants. Our system goes beyond mere detection, providing personalized cure recommendations based on learned the affected and diseased plants using deep learning models like convolutional neural networks (CNN) for early detection of diseases in plants. Deep learning approaches are used to classify and identify the diseases in plants and also the model which is best suited for early detection of plants is suited to give the correct and accurate output for the given plants. Early detection of plant diseases can be detected and recommend possible cures.

Plant Health Monitoring, Plant Disease, Image Processing, Deep Learning, CNN, Cure Recommendation

"A Survey on Plant Disease Detection Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.h715-h718, March-2024, Available :http://www.jetir.org/papers/JETIR2403795.pdf

"A Survey on Plant Disease Detection Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. pph715-h718, March-2024, Available at : http://www.jetir.org/papers/JETIR2403795.pdf